Algorithms and Programs of Dynamic Mixture Estimation

Unified Approach to Different Types of Components de

,

Éditeur :

Springer


Collection :

SpringerBriefs in Statistics

Paru le : 2017-08-14

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Description
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
Pages
113 pages
Collection
SpringerBriefs in Statistics
Parution
2017-08-14
Marque
Springer
EAN papier
9783319646701
EAN PDF
9783319646718

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
4086 Ko
Prix
52,74 €
EAN EPUB
9783319646718

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
2191 Ko
Prix
52,74 €